Zobrazeno 1 - 10
of 98
pro vyhledávání: '"Gyorgy Eigner"'
Autor:
Adam Gyula Nemes, Gyorgy Eigner
Publikováno v:
IEEE Access, Vol 12, Pp 170243-170249 (2024)
This paper presents an advanced approach for enhancing electroencephalography (EEG) classification accuracy in motor tasks through the integration of subject-specific features. Recognizing the significant challenge posed by inter-subject variability
Externí odkaz:
https://doaj.org/article/0e5f6feddffa46b2b90bf81d48f7b0d2
Publikováno v:
IEEE Access, Vol 12, Pp 168626-168644 (2024)
Activation functions are pivotal in neural networks, determining the output of each neuron. Traditionally, functions like sigmoid and ReLU have been static and deterministic. However, the introduction of parametric activation functions represents a s
Externí odkaz:
https://doaj.org/article/802306dd6ad94dd18bfeccda29d1e73d
Application of Deep Learning to Enhance Finger Movement Classification Accuracy From UHD-EEG Signals
Publikováno v:
IEEE Access, Vol 12, Pp 139937-139945 (2024)
This study investigates the classification of Ultra-High-Density Electroencephalography (UHD-EEG) signals corresponding to finger movements through the application of machine learning techniques, namely Support Vector Machines (SVM) and Multi-Layer P
Externí odkaz:
https://doaj.org/article/6d8cd72dc00a4cd1b42c545a7e47bf68
Publikováno v:
IEEE Access, Vol 12, Pp 16559-16572 (2024)
The rapid advancement of technology related to Industry 4.0 has brought about a paradigm shift in the way we interact with assets across various domains. This progress has led to the emergence of the concept of a Human Digital Twin (HDT), a virtual r
Externí odkaz:
https://doaj.org/article/ac3e1f6402de4197836876c097a6e4d4
Publikováno v:
IEEE Access, Vol 10, Pp 64348-64374 (2022)
The ongoing Industry 4.0 is characterized by the connectivity between components in the manufacturing system. For modern machines, the Internet of Things is a built-in function. In contrast, there are legacy machines in deployment functioning without
Externí odkaz:
https://doaj.org/article/64644097b2fc4ad9b9745c2ce608c36d
Publikováno v:
IEEE Access, Vol 9, Pp 143549-143563 (2021)
The state and disturbance estimations are an indispensable part of the state-of-the-art model-based controllers as related to the artificial pancreas, supporting the decision-making and self-tuning of the algorithms. They are not just important when
Externí odkaz:
https://doaj.org/article/8b2bbb8ea0634ae48a9aaa5d1b25554e
Publikováno v:
IEEE Access, Vol 7, Pp 125609-125622 (2019)
The current article investigates the possibilities of designing a robust control solution for a control problem related to type 1 diabetes mellitus. The proposed control methodology exploits linear parameter varying, linear matrix inequality, tensor
Externí odkaz:
https://doaj.org/article/62c49b8715844d26b991a8918fc3b1af
Publikováno v:
2023 IEEE 21st World Symposium on Applied Machine Intelligence and Informatics (SAMI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a28e015790dc6ba38d243d76b23744ab
https://doi.org/10.1109/sami58000.2023.10044504
https://doi.org/10.1109/sami58000.2023.10044504
Autor:
László Barkai, Melinda Bicsák, Katalin Muriová, Péter Dombrovsky, Levente Kovács, Gyorgy Eigner, Oliver Rácz
Publikováno v:
Orvosi Hetilap. 162:1652-1657
Összefoglaló. Bevezetés: A HbA1c integrált retrospektív mutatója az elmúlt időszak vércukrának, rendszeres vizsgálata a cukorbetegek anyagcserekontrolljának megítélésében elengedhetetlen. Helyes értékelése azonban nem egyszerű, me
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5501862c893362dc653a88744e53eb92
https://doi.org/10.1556/650.2021.32203
https://doi.org/10.1556/650.2021.32203
Autor:
Lehel Denes-Fazakas, Mate Siket, Gabor Kertesz, Laszlo Szilagyi, Levente Kovacs, Gyorgy Eigner
Publikováno v:
2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1602233b042491bafd9a778a0a219ba
https://doi.org/10.1109/smc53654.2022.9945084
https://doi.org/10.1109/smc53654.2022.9945084